Logo
Sign in

Integrated suite for qualitative, content, and statistical analysis, enabling exploration and coding of structured and unstructured data in one platform.

Vendor

Vendor

Provalis Research

Company Website

Company Website

Cluster-Extraction-min-2-1024x691.png
6-1024x619.png
Relate-text-structured-data-1024x676.jpg
QDA-Miner-on-screen-coding-1024x676.jpg
Product details

ProSuite by Provalis Research is a bundled suite of text analytics tools—QDA Miner, WordStat, and SimStat—designed to enable researchers and analysts to explore, code, and analyze both structured (numerical, categorical) and unstructured (text, images) data within a unified environment. The suite supports advanced computer-assisted qualitative coding, powerful content analysis and text mining, and comprehensive statistical analysis. ProSuite’s interoperability allows seamless movement between qualitative and quantitative data, supporting mixed-methods research and enabling users to relate text with structured data, perform GIS mapping, and conduct advanced clustering and categorization. The platform is suitable for academic, business, and government users who require flexible, transparent, and reproducible analytics workflows.

Key Features

Integrated Qualitative, Content, and Statistical Analysis Combines QDA Miner, WordStat, and SimStat for comprehensive data analysis.

  • Qualitative coding of text and images
  • Content analysis and text mining with dictionary and AI support
  • Statistical analysis of numerical and categorical data

Advanced Search and Coding Tools Facilitates efficient data exploration and coding.

  • Multiple text search tools (keyword, query-by-example, section retrieval)
  • Automated and manual coding options
  • Coding reliability assessment and project merging

Text Categorization and Clustering Enables sophisticated topic and concept discovery.

  • Hierarchical clustering and multidimensional scaling
  • Document and concept categorization using custom or pre-built dictionaries
  • Naïve-Bayes and k-nearest neighbor classification

Mixed-Methods and Data Integration Supports analysis across data types and research approaches.

  • Relate text with structured data (e.g., survey responses, metadata)
  • GIS mapping for spatial analysis of coded data
  • Seamless movement between qualitative and quantitative modules

Visualization and Reporting Provides interactive and customizable outputs.

  • Interactive maps, timelines, and charts
  • Export to Power BI and other reporting tools

Benefits

Comprehensive Mixed-Methods Research Enables integration of qualitative and quantitative data in a single workflow.

  • Analyze open-ended responses alongside numerical data
  • Relate textual themes to structured variables

Efficiency and Flexibility Streamlines research processes and adapts to diverse needs.

  • Automated coding and clustering tools save time
  • Flexible import/export and integration with external tools

Transparency and Reproducibility Ensures reliable and auditable research outcomes.

  • Transparent workflows and output management
  • Scripting and automation for reproducible analysis